Planning Grant: I/UCRC Center for UAS Site Addition (Virginia Tech)

无人机系统中心（C-UAS）是由杨百翰大学和科罗拉多大学于2012年成立的一个行业/大学合作研究中心（I/UCRC），为无人机行业面临的关键技术挑战提供创新解决方案，并为这一新兴领域培养多元化，高素质的领导干部。在寻求加入C-UAS，作为第三个大学网站，弗吉尼亚理工大学带来了各种关键和互补的研究领域的专业知识。弗吉尼亚理工大学还领导着美国联邦航空局指定的六个无人驾驶飞机系统测试场地之一，这为C-UAS合作伙伴提供了一个机会，以支持美国联邦航空局的监管政策制定工作，同时在新兴商业市场建立立足点。这项规划拨款支持弗吉尼亚理工大学努力开发一个可行的，自我维持的网站添加到C-UAS。具体的研究议程，以解决在此C-UAS网站添加将最终由中心的行业咨询委员会（IAB），包括谁承诺加入该中心的新代表沿着与弗吉尼亚理工大学。扩展的C-UAS研究计划可能的重点领域包括先进的飞行控制（例如，构造鲁棒的、安全的和数学上认证的控制算法的方法），农业（例如，监测植物病原体运输的方法），机器视觉和机器学习（例如，用于实时、机载智能图像处理的软件），多物理场设计优化（例如，包括非定常流体/结构相互作用的飞行器设计优化工具），安全性和适航性（例如，结合了小型UAS固有的不精确不确定性的可靠性预测方法），以及无线通信（例如，使用软件定义的无线电和智能通信协议，使信息流适应环境条件）。具体研究任务的建议将与潜在的行业和政府合作伙伴协调制定，以确保这些合作伙伴充分参与这一过程并致力于研究计划。

The Center for Unmanned Aircraft Systems (C-UAS), an Industry/University Cooperative Research Center (I/UCRC) established by Brigham Young University and the University of Colorado in 2012, provides innovative solutions to key technical challenges facing the UAS industry and trains a diverse, highly qualified cadre of leaders for this emerging field. In seeking to join the C-UAS, as a third university site, Virginia Tech brings expertise in a variety of critical and complementary research areas. Virginia Tech also leads one of six FAA-designated unmanned aircraft system test sites, which presents an opportunity for C-UAS partners to support the FAA's regulatory policy development efforts while establishing a foothold in emerging commercial markets. This planning grant supports Virginia Tech's effort to develop a viable, self-sustaining Site Addition to the C-UAS.The specific research agenda to be addressed within this C-UAS Site Addition will ultimately be determined by the Center's Industry Advisory Board (IAB), including new representatives who commit to join the Center along with Virginia Tech. Likely focus areas for the expanded C-UAS research program include advanced flight control (e.g., methods to construct robust, secure, and mathematically certified control algorithms), agriculture (e.g., methods to monitor plant pathogen transport), machine vision and machine learning (e.g., software for real-time, on-board intelligent image processing), multiphysics design optimization (e.g., aircraft design optimization tools that incorporate unsteady fluid/structure interaction), safety and airworthiness (e.g., reliability prediction methods that incorporate imprecise uncertainties intrinsic to small UAS), and wireless communications (e.g., the use of software defined radio and intelligent communication protocols that adapt the information flow to the environmental conditions). Proposals for specific research tasks will be developed in coordination with prospective industry and government partners to ensure that those partners are fully engaged in the process and committed to the research program.